1

Contract Machine Learning Engineer Jobs in Charleston, WV

Senior Applied AI Engineer

Charleston, WV · Remote

$113K - $149K/yr

Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Engineering, Data Science, or a related technical discipline (or equivalent professional ...

VP of Data and AI

Charleston, WV · Remote

$251K - $346K/yr

Required Experience * 10+ years of progressive experience in AI, machine learning, data science, data engineering, or a related field, with 5+ years in a senior leadership role (Sr Director, VP) ...

As a Prompt Engineer, you will be a key member of our AI development team, responsible for ... Familiarity with machine learning frameworks and libraries like TensorFlow, PyTorch, or Hugging ...

Build services that expose machine learning and AI based products * Deploy and manage various ... Engineer, you will be employed by Lyra Health, Inc. The anticipated annual base salary range for ...

... Machine Learning Engineering, and Analytics. Success in this role means building a data foundation ... contracts and platform investments * Lead audits of existing integrations and automations, and ...

The platform is built on Databricks for machine learning and data science and on AWS for production ... This leader will manage experienced engineers and specialists with significant autonomy, help ...

... of hands-on machine learning / AI engineering experience * Proven experience architecting and delivering solutions across multiple technical domains, such as APIs and microservices, systems ...

We harness the power of AI and machine learning to tokenize and secure digital identities, helping ... Key Responsibilities 1. High-Value Contract Negotiation & Drafting Lead direct negotiations with ...

Senior Data Scientist

Charleston, WV · Remote

$97K - $124K/yr

... other programming languages used for data science purposes * Ability to collaborate closely with business and technical leaders. * Ability to work with machine learning frameworks, such as ...

Showing results 21-40

Contract Machine Learning Engineer information

See Charleston, WV salary details

$30.6K

$125.1K

$188.1K

How much do contract machine learning engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for contract machine learning engineer in Charleston, WV is $125,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $150,600.00 per year, depending on experience, location, and employer.

What is a contract machine learning engineer?

A Contract Machine Learning Engineer is a professional who builds and deploys machine learning models on a temporary or project-based basis. They typically work with companies seeking specialized expertise in data science, model development, or AI integration without committing to a full-time hire. Responsibilities may include data preprocessing, model training, algorithm optimization, and deployment. Contract roles allow for flexibility and are often remote, making them ideal for businesses with short-term AI needs or startups looking to scale their machine learning capabilities quickly.

What are the typical day-to-day responsibilities of a contract machine learning engineer?

As a Contract Machine Learning Engineer, your daily tasks usually involve gathering and preprocessing data, building and fine-tuning machine learning models, and collaborating with software engineers and product managers to integrate your models into production systems. You may also meet with clients or internal teams to gather requirements and provide technical insights, as well as document and present your findings to stakeholders. Work is typically project-based and may require a high degree of independence, flexibility, and adaptability. This dynamic environment often exposes you to a variety of industries and technical challenges, making each project unique and providing valuable experience for professional growth.

What are the key skills and qualifications needed to thrive in the contract machine learning engineer position, and why are they important?

To thrive as a Contract Machine Learning Engineer, you need a strong background in machine learning algorithms, data preprocessing, statistical analysis, and proficiency in programming languages such as Python or R, often supported by a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms (AWS, Google Cloud, Azure) or certifications in these areas are common requirements. Excellent problem-solving, communication, and time management skills are vital, especially when working with cross-functional teams and managing multiple projects remotely. These skills ensure effective delivery of high-quality, scalable machine learning solutions within tight project timelines and diverse client environments.

What are popular job titles related to Contract Machine Learning Engineer jobs in Charleston, WV? For Contract Machine Learning Engineer jobs in Charleston, WV, the most frequently searched job titles are:
What cities near Charleston, WV are hiring for Contract Machine Learning Engineer jobs? Cities near Charleston, WV with the most Contract Machine Learning Engineer job openings:
Infographic showing various Contract Machine Learning Engineer job openings in Charleston, WV as of June 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $125,147 per year, or $60.2 per hour.

Senior Applied AI Engineer

LTS

Charleston, WV • Remote

$113K - $149K/yr

Full-time

Posted 5 days ago


Job description

Location: United States – Remote
Clearance: Ability to obtain and maintain a Public Trust

LTS is seeking a highly skilled Senior Applied AI Engineer to focus on continuously improving the intelligence behind the platform. You'll experiment with models, optimize retrieval strategies, refine agent reasoning, evaluate AI performance, and transform emerging AI capabilities into production-ready solutions.

The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today.

Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning.

We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide.

The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements.

The platform has executive sponsorship, committed users, and a customer investing in long-term modernization. Our engineering team is intentionally small giving every engineer meaningful ownership, and direct influence over product direction.

We don't simply build AI-powered software—we build software with AI. This is not another chatbot.

Using LLMs, autonomous agents, AI-assisted development, parallel workflows, and model-driven engineering is simply how we work.

What You'll Do:

Advance Applied AI Capabilities

  • Design, prototype, and implement production-ready AI capabilities that improve reasoning, accuracy, explainability, and developer productivity.
  • Evaluate emerging LLMs, multimodal models, agent frameworks, and AI techniques to identify opportunities for platform advancement.
  • Rapidly prototype new AI capabilities and transition successful experiments into production.

Optimize Agent Performance

  • Improve autonomous and multi-agent workflows through prompt engineering, reasoning optimization, memory strategies, tool selection, and context management.
  • Continuously refine Retrieval-Augmented Generation (RAG) pipelines, retrieval strategies, embeddings, reranking, and grounding techniques.
  • Improve AI response quality through experimentation, benchmarking, and iterative optimization.

Evaluate AI Systems

  • Develop evaluation frameworks that measure accuracy, groundedness, explainability, latency, and overall AI effectiveness.
  • Build benchmark datasets, automated evaluation pipelines, and performance metrics for production AI systems.
  • Analyze AI failures, hallucinations, retrieval gaps, and reasoning errors to drive continuous improvement.

Knowledge Engineer

  • Collaborate with software engineers to improve knowledge ingestion, document processing, semantic search, embeddings, and enterprise knowledge management.
  • Design approaches that maximize retrieval quality across large technical documentation and source code repositories.
  • Improve how AI agents discover, organize, and reason over enterprise knowledge.

Collaborate Across Engineer

  • Partner closely with AI architects, platform engineers, software engineers, and front-end engineers to improve the overall intelligence of the platform.
  • Share research findings, experimental results, and engineering recommendations with cross-functional teams.
  • Help establish best practices for experimentation, evaluation, and AI quality throughout the organization.

What We're Looking For:

  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Engineering, Data Science, or a related technical discipline (or equivalent professional experience).
  • 5+ years of software engineering, applied AI, machine learning, or AI systems development experience.
  • Demonstrated experience developing production AI applications powered by Large Language Models (LLMs).
  • Experience designing and optimizing Retrieval-Augmented Generation (RAG) systems.
  • Experience with prompt engineering, embeddings, semantic search, vector databases, and knowledge retrieval.
  • Experience evaluating AI model performance and implementing experimentation frameworks.
  • Strong programming skills in Python and experience with modern software engineering practices.
  • Experience with AI frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar.
  • Experience with using AI coding assistants as part of your daily workflow.
  • Familiarity with REST APIs, cloud-native applications, and distributed software systems.
  • Strong analytical, problem-solving, and communication skills.
  • Intellect and curiosity for AI systems and how they behave.
  • Deep passion for experimenting with new AI techniques.
  • Background in evaluation, explainability, and continuous improvement.
  • Proven success with ownership of difficult technical challenges and collaboration across disciplines.

Nice to Have:

  • Experience optimizing autonomous or multi-agent AI systems.
  • Experience implementing automated AI evaluation frameworks.
  • Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or open-source LLMs.
  • Experience with vector databases including Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search.
  • Experience with Responsible AI, AI governance, safety, and explainability.
  • Familiarity with software engineering tools, code intelligence platforms, or developer productivity solutions.
  • Experience supporting healthcare, Federal Government, or other highly regulated environments.
  • Experience using AI coding assistants and autonomous agents as part of daily software development.

What's In It for You?

  • The Opportunity to support high-visibility federal missions
  • A culture that values innovation, growth, and collaboration
  • Access to cutting-edge tools and technologies
  • Comprehensive benefits for you and your family
  • A career path that rewards ambition and performance

If you're ready to push boundaries, sharpen your skills, and join a team that is passionate about building what's next, we'd love to meet you. Apply today and let's build a future together!

LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements.

LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.